Evaluation of Moisture Damage under Crack-Sealed Asphalt Pavements in Louisiana

Transportation Research Record

Mousa

Gaspard³

2022

Self Cite

Extreme weather events, including inundation, are the major causes of weather-related disruption to the transportation sector. Considerable research has been conducted in recent years to evaluate the impacts of inundation on pavement functional and structural conditions. Yet, limited studies quantified how inundation may affect the long-term pavement performance and pavement life-cycle costs. As such, the main objective of this study was to quantify the impact of the 2016 inundation event in Louisiana, U.S., on the long-term pavement performance (in relation to reduction in the pavement service life [PSL]) and on pavement life-cycle costs. To achieve this objective, a total of 10 inundated pavement sections were evaluated. Pavement conditions, fatigue, and rutting indices for these sections were analyzed over a monitoring period of up to 15 years (11 years before and 4 years after inundation). Results indicated that the 2016 inundation event reduced the PSL of the inundated sections to an extent that depended on their pre-flooding pavement condition, traffic level, and asphalt concrete thickness. This reduction was attributed to the accelerated fatigue, rutting damage, or both, that resulted from prolonged water submergence and heavy traffic loading during debris hauling that took place after the inundation event. A logistic regression model with adequate accuracy was developed to predict whether an inundated pavement would experience reduction in its PSL based on the project conditions. The study findings were incorporated into a simple tool to assist transportation agencies make effective decisions for the maintenance and rehabilitation of inundated pavements.

Section: Expected Pavement Moisture Damage As a Results Of Water Subm...mentioning

confidence: 99%

Section: Expected Pavement Moisture Damage As a Results Of Water Subm...mentioning

confidence: 99%

See 1 more Smart Citation

Impact of the Great Flood of 2016 on the Asphaltic Concrete Road Infrastructure in Louisiana

Transportation Research Record

Mousa

Gaspard³

2022

Self Cite

“…Based on finite element analysis, it was reported that crack sealing could be applied under common rain intensities in Louisiana and for any groundwater depth without the potential for stripping (owing to moisture entrapment) if: (a) the permeability of the original pavement does not exceed 2 × 10 −6 m/s; and (b) crack sealing is applied after an extended dry period ( 26 ).…”

Section: Data Collectionmentioning

confidence: 99%

Development of a Decision-Making Tool to Select Optimum Preventive Maintenance Treatments in a Hot and Humid Climate

Mousa

Transportation Research Record

Zhang

et al. 2020

Self Cite

Preventive maintenance treatments are widely used throughout the United States to extend pavement service life (PSL), and therefore, defer costly rehabilitation activities. However, optimizing the use of these treatments faces several key challenges. First, the benefits resulting from these treatments are not well-defined. Second, there is considerable debate over the optimal timing of these treatments. Third, concerns exist that these treatments may be responsible for moisture damage if the surrounding moisture conditions are not adequately considered before installation. Although significant research has been conducted to address these challenges, few efforts have been directed toward technology transfer and implementation of the research findings. Therefore, the objective of this study was to combine the results of a comprehensive research study addressing these challenges into an enhanced decision-making tool that can be used to select the best maintenance treatment to be applied to an existing asphalt concrete (AC) overlay based on the project conditions. For a given project, this tool will predict the most cost-effective maintenance treatment (crack sealing, chip seal, microsurfacing, or do nothing) to address existing surface distresses without causing moisture damage. The tool will also provide the optimal timing of installation of the recommended treatment. To ensure that the developed tool is practical and simple to use, it was developed using macros in Microsoft Excel. The developed tool is implementation-ready and should be utilized by the relevant Department of Transportation to maximize the benefits from pavement maintenance activities.

“…It has been used extensively to simulate many drainage problems in geotechnical engineering and other disciplines, given its accuracy ( 17 ). Mousa et al ( 18 ) utilized the results of a calibrated SEEP/W model to introduce guidelines for using crack-sealing while minimizing water entrapment under cracks for low-volume roads.…”

Section: Introductionmentioning

confidence: 99%

Investigating the Seepage Characteristics of an Open-Graded Friction Course Using Finite Element Modeling

Abohamer

Transportation Research Record: Journal of the Transportation R

Mayeux

et al. 2023

Self Cite

An open-graded friction course (OGFC) is an asphalt mixture designed with a large air void (AV) content that provides enhanced drainage capability at the surface. The main objectives of this study were to investigate the impacts of selected factors (i.e., the OGFC thickness and coefficient of permeability, the permeability of the underlying layer, and traffic loading) on the drainage characteristics of the OGFC, develop a quantitative tool to simulate the deterioration in the functional performance of the OGFC, and propose new guidelines for the AV content of OGFC for optimum functionality. To this end, a three-dimensional finite element (FE) model was developed to evaluate the impacts of OGFC permeability, OGFC layer thickness, underlying layer permeability, rain intensity, and traffic volume on the seepage characteristics of OGFC pavements. The impacts of these factors were evaluated by calculating the time at which the OGFC surface reaches overflow condition ( TC). Statistical analysis of the results showed that all considered factors had a significant impact on OGFC seepage characteristics, except OGFC permeability. In addition, an artificial neural network (ANN) model was developed to predict TC without the need for FE modeling. Results indicated that the ANN model predicted TC accurately with R2 values of 0.99 and 0.98 in the training and validation stages, respectively. The results also indicated that the model accurately predicted TC over time for OGFC pavements with a root-mean-square error of less than 5.0%. Simulation runs were conducted using the developed FE model under different OGFC AV content conditions and rain intensities. Results revealed that an OGFC layer with an AV content of 16% would provide adequate drainage performance while minimizing OGFC durability issues.